activity
20232026
most citedCoFiI2P: Coarse-to-Fine Correspondences for Image-to-Point Cloud Registration

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Aerial-ground LiDAR place recognition with patch-level self-supervised learning and expanded reciprocal re-ranking

Yandi Yang, Xianghong Zou, Jianping Li +4

LiDAR place recognition determines one's position on a prior point cloud map. The most studied ground-level LiDAR place recognition suffers from pre-visit requirements, incomplete…

cs.CV2026

WHU-PCPR: A cross-platform heterogeneous point cloud dataset for place recognition in complex urban scenes

Xianghong Zou, Jianping Li, Yandi Yang +4

Point Cloud-based Place Recognition (PCPR) demonstrates considerable potential in applications such as autonomous driving, robot localization and navigation, and map update. In pra…

cs.CV2025

LifelongPR: Lifelong point cloud place recognition based on sample replay and prompt learning

Xianghong Zou, Jianping Li, Zhe Chen +4

Point cloud place recognition (PCPR) determines the geo-location within a prebuilt map and plays a crucial role in geoscience and robotics applications such as autonomous driving,…

cs.RO2024

Reliable-loc: Robust sequential LiDAR global localization in large-scale street scenes based on verifiable cues

Xianghong Zou, Jianping Li, Weitong Wu +3

Wearable laser scanning (WLS) system has the advantages of flexibility and portability. It can be used for determining the user's path within a prior map, which is a huge demand fo…

cs.CV2023★ 1 cited

CoFiI2P: Coarse-to-Fine Correspondences for Image-to-Point Cloud Registration

Shuhao Kang, Youqi Liao, Jianping Li +7

Image-to-point cloud (I2P) registration is a fundamental task for robots and autonomous vehicles to achieve cross-modality data fusion and localization. Current I2P registration me…